Overview

Dataset statistics

Number of variables81
Number of observations7161
Missing cells14030
Missing cells (%)2.4%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory4.4 MiB
Average record size in memory648.0 B

Variable types

BOOL40
CAT25
NUM16

Warnings

Dataset has 1 (< 0.1%) duplicate rows Duplicates
aa2 is highly correlated with aaHigh correlation
aa is highly correlated with aa2High correlation
CLEARANCE is highly correlated with CLEARANCECOCKHigh correlation
CLEARANCECOCK is highly correlated with CLEARANCEHigh correlation
SURG is highly correlated with PROCEDUREHigh correlation
PROCEDURE is highly correlated with SURGHigh correlation
CLEARANCECOCK has 83 (1.2%) missing values Missing
LVEF has 100 (1.4%) missing values Missing
PAPSYST has 3604 (50.3%) missing values Missing
LVEFISOTOPIC has 6570 (91.7%) missing values Missing
ETIOLOGY has 3548 (49.5%) missing values Missing
NUMBER has 6471 (90.4%) zeros Zeros
ANGORCLASSECCS has 5388 (75.2%) zeros Zeros

Reproduction

Analysis started2020-11-30 20:51:29.972423
Analysis finished2020-11-30 20:53:32.381275
Duration2 minutes and 2.41 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

ES1
Real number (ℝ≥0)

Distinct1971
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.358989163
Minimum0.8810525718
Maximum88.48248395
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:32.531188image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.8810525718
5-th percentile1.005392068
Q12.08257992
median4.446640765
Q38.627906637
95-th percentile23.85775344
Maximum88.48248395
Range87.60143138
Interquartile range (IQR)6.545326718

Descriptive statistics

Standard deviation9.430793872
Coefficient of variation (CV)1.281533871
Kurtosis18.91933507
Mean7.358989163
Median Absolute Deviation (MAD)2.712650122
Skewness3.732709619
Sum52697.7214
Variance88.93987306
MonotocityNot monotonic
2020-11-30T17:53:32.736074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.5054309613575.0%
 
0.88105257182924.1%
 
2.082579922703.8%
 
4.6480136841692.4%
 
1.5113518191371.9%
 
1.333689624761.1%
 
5.479038476711.0%
 
3.999065565670.9%
 
6.352257865530.7%
 
1.683913851510.7%
 
Other values (1961)561878.5%
 
ValueCountFrequency (%) 
0.88105257182924.1%
 
0.9411907096410.6%
 
1.005392068310.4%
 
1.073925311340.5%
 
1.147076038270.4%
 
ValueCountFrequency (%) 
88.482483951< 0.1%
 
86.373478941< 0.1%
 
85.882127531< 0.1%
 
84.879804621< 0.1%
 
84.471651451< 0.1%
 

ES2
Real number (ℝ≥0)

Distinct4802
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.172065942
Minimum0.49865156
Maximum94.42075474
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:32.945971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.49865156
5-th percentile0.6691633775
Q11.212919103
median2.432225922
Q35.054099811
95-th percentile18.17383107
Maximum94.42075474
Range93.92210318
Interquartile range (IQR)3.841180708

Descriptive statistics

Standard deviation9.078898446
Coefficient of variation (CV)1.75537175
Kurtosis28.79929218
Mean5.172065942
Median Absolute Deviation (MAD)1.481286023
Skewness4.83264105
Sum37037.16421
Variance82.42639699
MonotocityNot monotonic
2020-11-30T17:53:33.158831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.49865156941.3%
 
0.6733049492731.0%
 
0.6691633775490.7%
 
0.8041374276470.7%
 
0.580551453400.6%
 
0.6820668878340.5%
 
0.6743124659340.5%
 
2.755068384310.4%
 
3.308568087300.4%
 
0.5546841114300.4%
 
Other values (4792)669993.5%
 
ValueCountFrequency (%) 
0.49865156941.3%
 
0.501743134380.1%
 
0.513002866390.1%
 
0.527765015880.1%
 
0.53103612641< 0.1%
 
ValueCountFrequency (%) 
94.420754741< 0.1%
 
91.697916111< 0.1%
 
89.310710881< 0.1%
 
85.785110711< 0.1%
 
85.62182521< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
4869 
1
2292 
ValueCountFrequency (%) 
0486968.0%
 
1229232.0%
 
2020-11-30T17:53:33.305765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

AGEPAT
Real number (ℝ≥0)

Distinct77
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.65884653
Minimum18
Maximum94
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:33.439670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile37
Q155
median65
Q375
95-th percentile83
Maximum94
Range76
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.11496869
Coefficient of variation (CV)0.2217283136
Kurtosis0.1597510272
Mean63.65884653
Median Absolute Deviation (MAD)10
Skewness-0.6634702039
Sum455861
Variance199.2323411
MonotocityNot monotonic
2020-11-30T17:53:33.658544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
752213.1%
 
622203.1%
 
682153.0%
 
662092.9%
 
702062.9%
 
762022.8%
 
672022.8%
 
742022.8%
 
652002.8%
 
611982.8%
 
Other values (67)508671.0%
 
ValueCountFrequency (%) 
1870.1%
 
1980.1%
 
2090.1%
 
2190.1%
 
22180.3%
 
ValueCountFrequency (%) 
941< 0.1%
 
931< 0.1%
 
921< 0.1%
 
9170.1%
 
90110.2%
 

SMOKER
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
3481 
Past
2534 
Current
1116 
Unknown
 
30
ValueCountFrequency (%) 
No348148.6%
 
Past253435.4%
 
Current111615.6%
 
Unknown300.4%
 
2020-11-30T17:53:33.865427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:33.982356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:34.115280image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length4
Mean length3.50788996
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
Yes
4025 
No
3136 
ValueCountFrequency (%) 
Yes402556.2%
 
No313643.8%
 
2020-11-30T17:53:34.221221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

DIABETES STATUS
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
5349 
oral therapy
1247 
Insulin
565 
ValueCountFrequency (%) 
No534974.7%
 
oral therapy124717.4%
 
Insulin5657.9%
 
2020-11-30T17:53:34.333157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:34.443114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:34.565044image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length2
Mean length4.135874878
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
Yes
3591 
No
3570 
ValueCountFrequency (%) 
Yes359150.1%
 
No357049.9%
 
2020-11-30T17:53:34.658990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
4425 
Stable angina
1279 
Non STEMI
735 
STEMI
722 
ValueCountFrequency (%) 
No442561.8%
 
Stable angina127917.9%
 
Non STEMI73510.3%
 
STEMI72210.1%
 
2020-11-30T17:53:34.781919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:34.902831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:35.033756image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length4.985616534
Min length2

ACS<>
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
< 7 D
6082 
< 90 D
 
605
> 90 D
 
474
ValueCountFrequency (%) 
< 7 D608284.9%
 
< 90 D6058.4%
 
> 90 D4746.6%
 
2020-11-30T17:53:35.185688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:35.287628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:35.401564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length5
Mean length5.15067728
Min length5
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6298 
Yes
863 
ValueCountFrequency (%) 
No629887.9%
 
Yes86312.1%
 
2020-11-30T17:53:35.502506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

RECENTMI_A
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6167 
1
994 
ValueCountFrequency (%) 
0616786.1%
 
199413.9%
 
2020-11-30T17:53:35.555475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6436 
Valvular
 
574
CABG
 
68
Others
 
53
Combined
 
30
ValueCountFrequency (%) 
No643689.9%
 
Valvular5748.0%
 
CABG680.9%
 
Others530.7%
 
Combined300.4%
 
2020-11-30T17:53:35.665412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:35.777348image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:35.914249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length2
Mean length2.554671135
Min length2

NUMBER
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.1272346369
Minimum0
Maximum5
Zeros6471
Zeros (%)90.4%
Memory size55.9 KiB
2020-11-30T17:53:36.046193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4350686279
Coefficient of variation (CV)3.419419732
Kurtosis21.32691249
Mean0.1272346369
Median Absolute Deviation (MAD)0
Skewness4.195864031
Sum911
Variance0.189284711
MonotocityNot monotonic
2020-11-30T17:53:36.176120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
0647190.4%
 
15167.2%
 
21311.8%
 
3370.5%
 
43< 0.1%
 
52< 0.1%
 
(Missing)1< 0.1%
 
ValueCountFrequency (%) 
0647190.4%
 
15167.2%
 
21311.8%
 
3370.5%
 
43< 0.1%
 
ValueCountFrequency (%) 
52< 0.1%
 
43< 0.1%
 
3370.5%
 
21311.8%
 
15167.2%
 
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6178 
Carotid >50%
 
382
Lower Limbs
 
337
Previous vascular surgery
 
264
ValueCountFrequency (%) 
No617886.3%
 
Carotid >50%3825.3%
 
Lower Limbs3374.7%
 
Previous vascular surgery2643.7%
 
2020-11-30T17:53:36.333030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:36.434971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:36.558900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length25
Median length2
Mean length3.804915515
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6178 
1
983 
ValueCountFrequency (%) 
0617886.3%
 
198313.7%
 
2020-11-30T17:53:36.659824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6035 
Yes
1126 
ValueCountFrequency (%) 
No603584.3%
 
Yes112615.7%
 
2020-11-30T17:53:36.713791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6937 
Yes
 
224
ValueCountFrequency (%) 
No693796.9%
 
Yes2243.1%
 
2020-11-30T17:53:36.768760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6739 
Stroke
 
259
Peripheral
 
101
Visceral
 
47
Thrombosis
 
15
ValueCountFrequency (%) 
No673994.1%
 
Stroke2593.6%
 
Peripheral1011.4%
 
Visceral470.7%
 
Thrombosis150.2%
 
2020-11-30T17:53:36.884713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:37.001628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:37.144546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length2
Mean length2.313643346
Min length2

PREVIOUS STROKE
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6559 
Ischemic stroke
 
341
TIA
 
199
Hemorragic stroke
 
62
ValueCountFrequency (%) 
No655991.6%
 
Ischemic stroke3414.8%
 
TIA1992.8%
 
Hemorragic stroke620.9%
 
2020-11-30T17:53:37.311468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:37.415411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:37.557328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length2
Mean length2.776707164
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6949 
Yes
 
212
ValueCountFrequency (%) 
No694997.0%
 
Yes2123.0%
 
2020-11-30T17:53:37.663266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6949 
1
 
212
ValueCountFrequency (%) 
0694997.0%
 
12123.0%
 
2020-11-30T17:53:37.719216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

COPD
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6466 
Yes treated
 
413
Untreaded
 
282
ValueCountFrequency (%) 
No646690.3%
 
Yes treated4135.8%
 
Untreaded2823.9%
 
2020-11-30T17:53:37.836149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:37.944106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:38.051045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length2
Mean length2.794721408
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6748 
1
 
413
ValueCountFrequency (%) 
0674894.2%
 
14135.8%
 
2020-11-30T17:53:38.147989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

ULCER
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6852 
Yes
 
309
ValueCountFrequency (%) 
No685295.7%
 
Yes3094.3%
 
2020-11-30T17:53:38.201939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

NEOPLASIA
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6596 
<5years
 
469
no metatstasis
 
76
metatstasis
 
20
ValueCountFrequency (%) 
No659692.1%
 
<5years4696.5%
 
no metatstasis761.1%
 
metatstasis200.3%
 
2020-11-30T17:53:38.309875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:38.412837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:38.536749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length2
Mean length2.479960899
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
7025 
Yes
 
136
ValueCountFrequency (%) 
No702598.1%
 
Yes1361.9%
 
2020-11-30T17:53:38.636689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

CIRRHOSIS
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
7086 
Uncomplicated
 
45
PHT
 
30
ValueCountFrequency (%) 
No708699.0%
 
Uncomplicated450.6%
 
PHT300.4%
 
2020-11-30T17:53:38.755623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:38.869555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:38.983513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length2.073313783
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
7090 
Yes
 
71
ValueCountFrequency (%) 
No709099.0%
 
Yes711.0%
 
2020-11-30T17:53:39.081453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

WEIGHT
Real number (ℝ≥0)

Distinct103
Distinct (%)1.4%
Missing14
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean75.41332027
Minimum32
Maximum157
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:39.195388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile52
Q165
median75
Q385
95-th percentile101
Maximum157
Range125
Interquartile range (IQR)20

Descriptive statistics

Standard deviation15.02153996
Coefficient of variation (CV)0.1991894788
Kurtosis0.5547569729
Mean75.41332027
Median Absolute Deviation (MAD)10
Skewness0.464317533
Sum538979
Variance225.6466627
MonotocityNot monotonic
2020-11-30T17:53:39.393275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
704005.6%
 
803955.5%
 
753054.3%
 
602363.3%
 
652343.3%
 
852112.9%
 
782022.8%
 
901942.7%
 
721942.7%
 
681872.6%
 
Other values (93)458964.1%
 
ValueCountFrequency (%) 
321< 0.1%
 
341< 0.1%
 
352< 0.1%
 
362< 0.1%
 
372< 0.1%
 
ValueCountFrequency (%) 
1571< 0.1%
 
1551< 0.1%
 
1402< 0.1%
 
1362< 0.1%
 
1332< 0.1%
 

HEIGHT
Real number (ℝ≥0)

Distinct65
Distinct (%)0.9%
Missing26
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean168.437281
Minimum135
Maximum205
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:39.595159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile153
Q1162
median169
Q3175
95-th percentile183
Maximum205
Range70
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.462641662
Coefficient of variation (CV)0.05617902168
Kurtosis0.03661775305
Mean168.437281
Median Absolute Deviation (MAD)6
Skewness-0.003011178523
Sum1201800
Variance89.54158722
MonotocityNot monotonic
2020-11-30T17:53:39.799022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1706348.9%
 
1604626.5%
 
1654496.3%
 
1753855.4%
 
1803474.8%
 
1723124.4%
 
1682834.0%
 
1732693.8%
 
1762313.2%
 
1692263.2%
 
Other values (55)353749.4%
 
ValueCountFrequency (%) 
1352< 0.1%
 
140120.2%
 
14140.1%
 
14260.1%
 
1432< 0.1%
 
ValueCountFrequency (%) 
20540.1%
 
2041< 0.1%
 
2021< 0.1%
 
2002< 0.1%
 
1993< 0.1%
 

BMI
Real number (ℝ≥0)

Distinct1933
Distinct (%)27.1%
Missing26
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean26.52604052
Minimum11.97954711
Maximum50.21913806
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:40.011921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11.97954711
5-th percentile19.80073053
Q123.45091822
median25.97867957
Q329.06976744
95-th percentile34.83099252
Maximum50.21913806
Range38.23959094
Interquartile range (IQR)5.618849223

Descriptive statistics

Standard deviation4.618359619
Coefficient of variation (CV)0.1741066337
Kurtosis1.177608093
Mean26.52604052
Median Absolute Deviation (MAD)2.795288563
Skewness0.7127276091
Sum189263.2991
Variance21.32924557
MonotocityNot monotonic
2020-11-30T17:53:40.275751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
24.22145329550.8%
 
25.95155709470.7%
 
27.6816609460.6%
 
23.4375400.6%
 
24.69135802350.5%
 
25.71166208350.5%
 
27.34375340.5%
 
24.48979592330.5%
 
27.54820937290.4%
 
26.12244898280.4%
 
Other values (1923)675394.3%
 
ValueCountFrequency (%) 
11.979547111< 0.1%
 
13.427202791< 0.1%
 
13.590449951< 0.1%
 
14.429606161< 0.1%
 
14.605054971< 0.1%
 
ValueCountFrequency (%) 
50.219138061< 0.1%
 
49.60317461< 0.1%
 
48.487836951< 0.1%
 
48.456790121< 0.1%
 
47.839506171< 0.1%
 

CARDIAC RHYTHM
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
Sinusal
6311 
FA ou TSV
850 
ValueCountFrequency (%) 
Sinusal631188.1%
 
FA ou TSV85011.9%
 
2020-11-30T17:53:40.504637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:40.626569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:40.762491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length7
Mean length7.237397012
Min length7

NYHACLASS
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
3
2789 
4
2162 
1
1538 
2
672 
ValueCountFrequency (%) 
3278938.9%
 
4216230.2%
 
1153821.5%
 
26729.4%
 
2020-11-30T17:53:40.954360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:41.063319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:41.213213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

ANGORCLASSECCS
Real number (ℝ≥0)

ZEROS

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.567518503
Minimum0
Maximum4
Zeros5388
Zeros (%)75.2%
Memory size55.9 KiB
2020-11-30T17:53:41.363146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.051309692
Coefficient of variation (CV)1.852467692
Kurtosis1.066245211
Mean0.567518503
Median Absolute Deviation (MAD)0
Skewness1.568019201
Sum4064
Variance1.105252068
MonotocityNot monotonic
2020-11-30T17:53:41.528031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
0538875.2%
 
2100214.0%
 
35027.0%
 
11742.4%
 
4951.3%
 
ValueCountFrequency (%) 
0538875.2%
 
11742.4%
 
2100214.0%
 
35027.0%
 
4951.3%
 
ValueCountFrequency (%) 
4951.3%
 
35027.0%
 
2100214.0%
 
11742.4%
 
0538875.2%
 
Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size55.9 KiB
No
6781 
Yes
 
379
(Missing)
 
1
ValueCountFrequency (%) 
No678194.7%
 
Yes3795.3%
 
(Missing)1< 0.1%
 
2020-11-30T17:53:41.662953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6840 
yes
 
321
ValueCountFrequency (%) 
No684095.5%
 
yes3214.5%
 
2020-11-30T17:53:42.198666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6840 
1
 
321
ValueCountFrequency (%) 
0684095.5%
 
13214.5%
 
2020-11-30T17:53:42.261610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6943 
1
 
218
ValueCountFrequency (%) 
0694397.0%
 
12183.0%
 
2020-11-30T17:53:42.313601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

CREATININE
Real number (ℝ≥0)

Distinct318
Distinct (%)4.5%
Missing24
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean100.8492364
Minimum35
Maximum999
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:42.437514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile59
Q175
median88
Q3106
95-th percentile167
Maximum999
Range964
Interquartile range (IQR)31

Descriptive statistics

Standard deviation65.71462519
Coefficient of variation (CV)0.6516125214
Kurtosis69.87248762
Mean100.8492364
Median Absolute Deviation (MAD)15
Skewness7.134284169
Sum719761
Variance4318.411964
MonotocityNot monotonic
2020-11-30T17:53:42.638417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
851502.1%
 
881492.1%
 
761492.1%
 
801472.1%
 
751442.0%
 
771422.0%
 
821381.9%
 
891371.9%
 
861361.9%
 
781351.9%
 
Other values (308)571079.7%
 
ValueCountFrequency (%) 
3540.1%
 
372< 0.1%
 
381< 0.1%
 
392< 0.1%
 
401< 0.1%
 
ValueCountFrequency (%) 
99940.1%
 
9981< 0.1%
 
9901< 0.1%
 
9521< 0.1%
 
9491< 0.1%
 

CLEARANCECOCK
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct1431
Distinct (%)20.2%
Missing83
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean77.18650749
Minimum4.8
Maximum262.4
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:42.835301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum4.8
5-th percentile30.9
Q154.3
median73.7
Q396.1
95-th percentile134.8
Maximum262.4
Range257.6
Interquartile range (IQR)41.8

Descriptive statistics

Standard deviation32.30904975
Coefficient of variation (CV)0.4185841645
Kurtosis1.154076404
Mean77.18650749
Median Absolute Deviation (MAD)20.8
Skewness0.7221733017
Sum546326.1
Variance1043.874696
MonotocityNot monotonic
2020-11-30T17:53:43.051162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
88.5200.3%
 
72.1190.3%
 
73.4180.3%
 
47170.2%
 
64.3170.2%
 
95.8160.2%
 
76.9160.2%
 
63.6160.2%
 
57160.2%
 
108.1160.2%
 
Other values (1421)690796.5%
 
(Missing)831.2%
 
ValueCountFrequency (%) 
4.81< 0.1%
 
5.61< 0.1%
 
5.93< 0.1%
 
6.11< 0.1%
 
6.82< 0.1%
 
ValueCountFrequency (%) 
262.41< 0.1%
 
259.51< 0.1%
 
248.21< 0.1%
 
247.51< 0.1%
 
238.81< 0.1%
 

LVEF
Real number (ℝ≥0)

MISSING

Distinct72
Distinct (%)1.0%
Missing100
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean57.82495397
Minimum10
Maximum89
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:43.256040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile35
Q150
median60
Q366
95-th percentile75
Maximum89
Range79
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.06145526
Coefficient of variation (CV)0.2085856439
Kurtosis0.4235718472
Mean57.82495397
Median Absolute Deviation (MAD)8
Skewness-0.6533560646
Sum408302
Variance145.478703
MonotocityNot monotonic
2020-11-30T17:53:43.463941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
60144220.1%
 
557019.8%
 
706569.2%
 
506318.8%
 
654406.1%
 
453474.8%
 
402413.4%
 
351682.3%
 
301532.1%
 
681161.6%
 
Other values (62)216630.2%
 
ValueCountFrequency (%) 
101< 0.1%
 
152< 0.1%
 
161< 0.1%
 
171< 0.1%
 
20410.6%
 
ValueCountFrequency (%) 
892< 0.1%
 
883< 0.1%
 
872< 0.1%
 
8650.1%
 
8560.1%
 

PAPSYST
Real number (ℝ≥0)

MISSING

Distinct78
Distinct (%)2.2%
Missing3604
Missing (%)50.3%
Infinite0
Infinite (%)0.0%
Mean42.26595446
Minimum10
Maximum125
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:43.691791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile25
Q131
median40
Q350
95-th percentile70
Maximum125
Range115
Interquartile range (IQR)19

Descriptive statistics

Standard deviation14.28240801
Coefficient of variation (CV)0.3379175555
Kurtosis1.826459022
Mean42.26595446
Median Absolute Deviation (MAD)10
Skewness1.126757954
Sum150340
Variance203.9871786
MonotocityNot monotonic
2020-11-30T17:53:43.901690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
303605.0%
 
403544.9%
 
353164.4%
 
452813.9%
 
502723.8%
 
252293.2%
 
551442.0%
 
601422.0%
 
70781.1%
 
38771.1%
 
Other values (68)130418.2%
 
(Missing)360450.3%
 
ValueCountFrequency (%) 
101< 0.1%
 
121< 0.1%
 
141< 0.1%
 
1550.1%
 
162< 0.1%
 
ValueCountFrequency (%) 
1251< 0.1%
 
1201< 0.1%
 
1131< 0.1%
 
1102< 0.1%
 
1052< 0.1%
 

LVEFISOTOPIC
Real number (ℝ≥0)

MISSING

Distinct72
Distinct (%)12.2%
Missing6570
Missing (%)91.7%
Infinite0
Infinite (%)0.0%
Mean55.26565144
Minimum14
Maximum91
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:44.113568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile25.5
Q145
median57
Q366
95-th percentile79
Maximum91
Range77
Interquartile range (IQR)21

Descriptive statistics

Standard deviation15.30388744
Coefficient of variation (CV)0.2769149922
Kurtosis-0.3809770181
Mean55.26565144
Median Absolute Deviation (MAD)10
Skewness-0.4030498518
Sum32662
Variance234.2089707
MonotocityNot monotonic
2020-11-30T17:53:44.324428image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
60320.4%
 
55310.4%
 
65270.4%
 
50270.4%
 
70190.3%
 
64190.3%
 
40190.3%
 
69160.2%
 
45150.2%
 
54150.2%
 
Other values (62)3715.2%
 
(Missing)657091.7%
 
ValueCountFrequency (%) 
141< 0.1%
 
152< 0.1%
 
181< 0.1%
 
192< 0.1%
 
202< 0.1%
 
ValueCountFrequency (%) 
911< 0.1%
 
871< 0.1%
 
853< 0.1%
 
841< 0.1%
 
831< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
3633 
yes
3528 
ValueCountFrequency (%) 
No363350.7%
 
yes352849.3%
 
2020-11-30T17:53:44.472342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
Yes
4125 
No
3036 
ValueCountFrequency (%) 
Yes412557.6%
 
No303642.4%
 
2020-11-30T17:53:44.538328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
3673 
Ao stenosis
1744 
Org MR
794 
AoI
514 
Mitral stenosis
 
361
Other values (2)
 
75
ValueCountFrequency (%) 
No367351.3%
 
Ao stenosis174424.4%
 
Org MR79411.1%
 
AoI5147.2%
 
Mitral stenosis3615.0%
 
fctl MR470.7%
 
Tricuspid280.4%
 
2020-11-30T17:53:44.658238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:44.785183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:44.960083image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length2
Mean length5.422706326
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6644 
Yes
 
517
ValueCountFrequency (%) 
No664492.8%
 
Yes5177.2%
 
2020-11-30T17:53:45.076017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

TRICUSPID
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6435 
Yes
726 
ValueCountFrequency (%) 
No643589.9%
 
Yes72610.1%
 
2020-11-30T17:53:45.138980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

ETIOLOGY
Categorical

MISSING

Distinct7
Distinct (%)0.2%
Missing3548
Missing (%)49.5%
Memory size55.9 KiB
Degenerative/Dystrophic
2146 
rheumatic
660 
Endocarditis
363 
Congenital
252 
Others
 
182
Other values (2)
 
10
ValueCountFrequency (%) 
Degenerative/Dystrophic214630.0%
 
rheumatic6609.2%
 
Endocarditis3635.1%
 
Congenital2523.5%
 
Others1822.5%
 
Inflammatory 90.1%
 
others1< 0.1%
 
(Missing)354849.5%
 
2020-11-30T17:53:45.246898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-30T17:53:45.364835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:45.540750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length23
Median length6
Mean length10.33836056
Min length3

REDO_A
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6603 
Autre
 
162
Mitral valve repair failure
 
123
bioproth. failure
 
112
Endocarditis
 
75
Other values (3)
 
86
ValueCountFrequency (%) 
No660392.2%
 
Autre1622.3%
 
Mitral valve repair failure1231.7%
 
bioproth. failure1121.6%
 
Endocarditis751.0%
 
Prosthetic valve thrombosis520.7%
 
CABG280.4%
 
Yes60.1%
 
2020-11-30T17:53:45.735621image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:45.862545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:46.054456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length27
Median length2
Mean length3.042452171
Min length2

ASCENDINGAORTA
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6564 
Aneurysm
 
447
Dissection
 
150
ValueCountFrequency (%) 
No656491.7%
 
Aneurysm4476.2%
 
Dissection1502.1%
 
2020-11-30T17:53:46.217363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:46.326282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:46.456205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length2
Mean length2.542103058
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
7071 
Yes
 
90
ValueCountFrequency (%) 
No707198.7%
 
Yes901.3%
 
2020-11-30T17:53:46.570160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

OTHERS
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6990 
Others
 
85
Tumor
 
62
Pericarditis
 
18
DISSECTION TYPE B
 
4
Other values (2)
 
2
ValueCountFrequency (%) 
No699097.6%
 
Others851.2%
 
Tumor620.9%
 
Pericarditis180.3%
 
DISSECTION TYPE B40.1%
 
Transplantation1< 0.1%
 
Dissection1< 0.1%
 
2020-11-30T17:53:46.691091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-11-30T17:53:46.813002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:46.984923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length2
Mean length2.109900852
Min length2

URGENCY
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6752 
Yes
 
409
ValueCountFrequency (%) 
No675294.3%
 
Yes4095.7%
 
2020-11-30T17:53:47.104837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

URGENCY_A
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6752 
1
 
409
ValueCountFrequency (%) 
0675294.3%
 
14095.7%
 
2020-11-30T17:53:47.161803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
Yes
4135 
No
3026 
ValueCountFrequency (%) 
Yes413557.7%
 
No302642.3%
 
2020-11-30T17:53:47.224784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

AORTIC
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
4400 
Bioprosthesis
1729 
Mechanical
997 
valve repair
 
19
Homograft
 
15
ValueCountFrequency (%) 
No440061.4%
 
Bioprosthesis172924.1%
 
Mechanical99713.9%
 
valve repair190.3%
 
Homograft150.2%
 
Autogreffe1< 0.1%
 
2020-11-30T17:53:47.332723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-30T17:53:47.441640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:47.592574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length5.812037425
Min length2

MITRAL
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
5465 
Mechanical
662 
Bioprosthesis
556 
valve repair
 
475
Valve repair
 
3
ValueCountFrequency (%) 
No546576.3%
 
Mechanical6629.2%
 
Bioprosthesis5567.8%
 
valve repair4756.6%
 
Valve repair3< 0.1%
 
2020-11-30T17:53:47.970337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:48.173222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:48.440070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length4.261136713
Min length2

TRISCUPID
Categorical

Distinct5
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size55.9 KiB
No
6313 
valve repair
766 
Bioprosthesis
 
75
Homograft
 
3
Mechanical
 
3
ValueCountFrequency (%) 
No631388.2%
 
valve repair76610.7%
 
Bioprosthesis751.0%
 
Homograft3< 0.1%
 
Mechanical3< 0.1%
 
(Missing)1< 0.1%
 
2020-11-30T17:53:48.771878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:49.075710image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:49.446494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length3.191314062
Min length2

CABG
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
3739 
Yes
3422 
ValueCountFrequency (%) 
No373952.2%
 
Yes342247.8%
 
2020-11-30T17:53:49.622395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
No
6460 
Bentall mec
 
210
ascending aorta
 
156
Ascending+aortic valve
 
102
Ascending aorta+aortic valve repair
 
89
Other values (10)
 
144
ValueCountFrequency (%) 
No646090.2%
 
Bentall mec2102.9%
 
ascending aorta1562.2%
 
Ascending+aortic valve1021.4%
 
Ascending aorta+aortic valve repair891.2%
 
Bentall bio741.0%
 
Ascending and arch490.7%
 
ascending aorta-CABG50.1%
 
Bentall bio+PAC50.1%
 
Ascending aorta-valve repair50.1%
 
Other values (5)60.1%
 
2020-11-30T17:53:49.832270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)0.1%
2020-11-30T17:53:50.005194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length35
Median length2
Mean length3.514034353
Min length2

OTHERS.1
Categorical

Distinct7
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size55.9 KiB
No
6822 
Others
 
215
Tumor
 
63
Congenital
 
30
Myomectomy
 
27
Other values (2)
 
3
ValueCountFrequency (%) 
No682295.3%
 
Others2153.0%
 
Tumor630.9%
 
Congenital300.4%
 
Myomectomy270.4%
 
POF2< 0.1%
 
AF1< 0.1%
 
(Missing)1< 0.1%
 
2020-11-30T17:53:50.177073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-30T17:53:50.301021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:50.478899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length2
Mean length2.210585114
Min length2

WEIGHTOFPROC
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
Isolated CABG
2648 
single non CABG
2296 
2 procedures
1527 
3 procedures
690 
ValueCountFrequency (%) 
Isolated CABG264837.0%
 
single non CABG229632.1%
 
2 procedures152721.3%
 
3 procedures6909.6%
 
2020-11-30T17:53:50.652801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:50.794720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:51.068563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length13
Mean length13.33165759
Min length12
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6755 
1
 
406
ValueCountFrequency (%) 
0675594.3%
 
14065.7%
 
2020-11-30T17:53:51.298433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

D30DEATH
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6834 
1
 
327
ValueCountFrequency (%) 
0683495.4%
 
13274.6%
 
2020-11-30T17:53:51.400372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

aa
Real number (ℝ≥0)

HIGH CORRELATION

Distinct36
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.466834241
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:51.571274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median7
Q317
95-th percentile25
Maximum36
Range35
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.628800459
Coefficient of variation (CV)0.9114768717
Kurtosis-0.849702687
Mean9.466834241
Median Absolute Deviation (MAD)6
Skewness0.6287935395
Sum67792
Variance74.45619736
MonotocityNot monotonic
2020-11-30T17:53:51.812135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%) 
1246034.4%
 
172213.1%
 
42203.1%
 
102153.0%
 
82092.9%
 
122062.9%
 
182022.8%
 
92022.8%
 
162022.8%
 
72002.8%
 
Other values (26)282439.4%
 
ValueCountFrequency (%) 
1246034.4%
 
21782.5%
 
31982.8%
 
42203.1%
 
51862.6%
 
ValueCountFrequency (%) 
361< 0.1%
 
351< 0.1%
 
341< 0.1%
 
3370.1%
 
32110.2%
 

aa2
Real number (ℝ≥0)

HIGH CORRELATION

Distinct35
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.810361681
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:52.066990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q316
95-th percentile24
Maximum35
Range34
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.298418702
Coefficient of variation (CV)0.9418930802
Kurtosis-0.7591179466
Mean8.810361681
Median Absolute Deviation (MAD)5
Skewness0.697291225
Sum63091
Variance68.86375296
MonotocityNot monotonic
2020-11-30T17:53:52.337834image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%) 
1263836.8%
 
162213.1%
 
32203.1%
 
92153.0%
 
72092.9%
 
112062.9%
 
82022.8%
 
152022.8%
 
172022.8%
 
62002.8%
 
Other values (25)264637.0%
 
ValueCountFrequency (%) 
1263836.8%
 
21982.8%
 
32203.1%
 
41862.6%
 
51792.5%
 
ValueCountFrequency (%) 
351< 0.1%
 
341< 0.1%
 
331< 0.1%
 
3270.1%
 
31110.2%
 

redo
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6472 
1
689 
ValueCountFrequency (%) 
0647290.4%
 
16899.6%
 
2020-11-30T17:53:52.523731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mi
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
5704 
1
1457 
ValueCountFrequency (%) 
0570479.7%
 
1145720.3%
 
2020-11-30T17:53:52.607686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

delaimi
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
1
6687 
0
 
474
ValueCountFrequency (%) 
1668793.4%
 
04746.6%
 
2020-11-30T17:53:52.697628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6942 
1
 
219
ValueCountFrequency (%) 
0694296.9%
 
12193.1%
 
2020-11-30T17:53:52.775583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

ua
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
7066 
1
 
95
ValueCountFrequency (%) 
0706698.7%
 
1951.3%
 
2020-11-30T17:53:52.862533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6828 
1
 
333
ValueCountFrequency (%) 
0682895.3%
 
13334.7%
 
2020-11-30T17:53:52.942486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

lv1
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
7028 
1
 
133
ValueCountFrequency (%) 
0702898.1%
 
11331.9%
 
2020-11-30T17:53:53.018444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

lv2
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6009 
1
1152 
ValueCountFrequency (%) 
0600983.9%
 
1115216.1%
 
2020-11-30T17:53:53.099396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6460 
1
701 
ValueCountFrequency (%) 
0646090.2%
 
17019.8%
 
2020-11-30T17:53:53.176352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

PROCEDURE
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
1
4513 
0
2648 
ValueCountFrequency (%) 
1451363.0%
 
0264837.0%
 
2020-11-30T17:53:53.237319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6596 
1
 
565
ValueCountFrequency (%) 
0659692.1%
 
15657.9%
 
2020-11-30T17:53:53.303280image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

CLEARANCE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct6534
Distinct (%)91.6%
Missing31
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean77.18585061
Minimum5.551
Maximum262.728
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T17:53:53.446220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5.551
5-th percentile30.76777509
Q154.35928783
median73.67971429
Q396.13043243
95-th percentile134.9704459
Maximum262.728
Range257.177
Interquartile range (IQR)41.77114461

Descriptive statistics

Standard deviation32.35368883
Coefficient of variation (CV)0.4191660592
Kurtosis1.150594324
Mean77.18585061
Median Absolute Deviation (MAD)20.84662015
Skewness0.7232583889
Sum550335.1149
Variance1046.761181
MonotocityNot monotonic
2020-11-30T17:53:53.691061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
88.56110.2%
 
92.25110.2%
 
108.24100.1%
 
103.3290.1%
 
98.480.1%
 
94.7180.1%
 
95.9460.1%
 
102.0960.1%
 
46.860.1%
 
110.760.1%
 
Other values (6524)704998.4%
 
(Missing)310.4%
 
ValueCountFrequency (%) 
5.5511< 0.1%
 
5.857555111< 0.1%
 
5.8585308061< 0.1%
 
5.9394594591< 0.1%
 
6.0603141361< 0.1%
 
ValueCountFrequency (%) 
262.7281< 0.1%
 
259.80612241< 0.1%
 
248.461< 0.1%
 
247.82222221< 0.1%
 
239.08857141< 0.1%
 

SURG
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
1
4135 
0
2648 
2
 
378
ValueCountFrequency (%) 
1413557.7%
 
0264837.0%
 
23785.3%
 
2020-11-30T17:53:54.005878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T17:53:54.110816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:54.221755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Interactions

2020-11-30T17:52:12.931659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:13.527928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:13.709845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:14.231078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:14.430962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:14.606881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:14.830734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:15.057604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:15.664256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:16.929413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:17.137302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:17.358381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:17.579586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:18.017129image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:18.342925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:18.712934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:18.936917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:19.136883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:19.329977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:19.525927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:19.721921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:19.924829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:20.132940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:20.377894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:20.573888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:20.773892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:21.007113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:21.224918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:21.708781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:22.044131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:22.256010image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:22.563866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:22.748919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:22.969917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:23.170922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:23.373915image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:23.579911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:23.766922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:23.966861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:24.165867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:24.385871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:24.591966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:24.803940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:25.013875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:25.230825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:25.455939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:25.803959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:26.002938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:26.211936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:26.416910image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:26.634920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:26.843783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:27.064876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T17:52:35.020642image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:35.213531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T17:52:35.591313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:35.790220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:35.977092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:36.170981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:36.357875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T17:52:36.726672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:36.915557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T17:52:37.492243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:37.691113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:37.888995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:38.069912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:38.265781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:38.450674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:38.644583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:38.840451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:39.037337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:39.235226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:39.440106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:39.659001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:39.869862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:40.086735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:40.289619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:40.514494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:40.724390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:40.931253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:41.138135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:41.341037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:41.557913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:41.767772image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:41.977660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:42.181535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:42.369448image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:42.563317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:42.767200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:42.978080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:43.221939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:43.414827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:43.849598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:44.052461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:44.260365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:44.445236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:44.632130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:44.851004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:45.077874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:45.301746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:45.493639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:45.680531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:45.880416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:46.151259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:46.424103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:46.722938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:47.195323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:47.965406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:48.960987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:49.680581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:50.057359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:50.404161image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:50.754959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:51.256277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:52.104073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:52.429883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:52.961579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:53.436306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:53.894636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:54.401349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:54.842094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:55.560683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:56.873758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:57.661838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:58.214521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:58.588852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:58.790735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:59.011631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:59.196524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:59.438364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:52:59.637270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:00.511748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:00.703639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:00.895529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:01.075431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:01.248326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:01.417229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:01.596127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:01.768030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:01.946945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:02.116776image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:02.433574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:02.783374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:03.915031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:04.449650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:04.813443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:05.465138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:05.928873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:06.459599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:07.079184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:07.725706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:08.174451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:09.493388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:09.960860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:10.157748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:10.360630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:10.707095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:10.922967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:11.118857image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:11.307767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:11.493644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:11.672558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:12.043324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:12.284192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:12.485074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:12.993209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:13.211086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:13.400977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:13.579879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:13.762770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:13.928676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:14.208511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:14.445377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:14.633268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:14.805190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:14.975092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:15.139979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:15.309883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:15.476787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:15.674672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:15.839597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:16.004503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:16.182380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:16.342289image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:16.504197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:16.678096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T17:53:17.002933image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:17.181829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:17.353729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:17.522614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:17.690516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:17.857420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:18.030321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:18.198226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:18.359134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:18.520041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:18.691962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:18.867861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:19.035765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:19.226635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:19.441512image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:19.613433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:19.801307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:19.980223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:20.182088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:20.357988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:20.531906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:20.691815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:20.846726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:21.010632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:21.167545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:21.328430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-30T17:53:54.458637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-30T17:53:55.156238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-30T17:53:55.850819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-30T17:53:56.782287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-30T17:53:59.104955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-30T17:53:22.132971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:28.557287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:30.874139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T17:53:31.417848image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

ES1ES2GENDERPAT_AAGEPATSMOKERARTERIAL HYPERTENSIONDIABETES STATUSDYSLIPIDEMIACORONARY ARTERY DISEASEACS<>PREVIOUSANGIOPLASTYRECENTMI_APREVIOUS CARDIAC SURGERYNUMBEREXTRACARDIAC ARTERIOPATHYEXTRACARDIAC ARTERIOPATHY_APREVIOUS CARDIAC FAILUREPREVIOUS ENDOCARDITISPREVIOUSEMBOLICEVENTPREVIOUS STROKENEUROLOGIC DYSFUNCTIONNEUROLOGIC DYSFUNCTION_ACOPDCOPDEUROSC_AULCERNEOPLASIAPREVIOUSRADIOTHERAPYCIRRHOSISON DIALYSISWEIGHTHEIGHTBMICARDIAC RHYTHMNYHACLASSANGORCLASSECCSCARDIACFAILUREACTIVEENDOCARDITISACTIVEENDOCARDITIS_BCRITICALPREOPERATIVESTATE_ACREATININECLEARANCECOCKLVEFPAPSYSTLVEFISOTOPICCORONARYARTERYDISEASEVALVULOPATHYSINGLEVALVULOPATHYPOLYVALVULOPATHYTRICUSPIDETIOLOGYREDO_AASCENDINGAORTACONGENITALHEARTDISEASEOTHERSURGENCYURGENCY_AVALVULARSURGERYAORTICMITRALTRISCUPIDCABGASCENDINGAORTASURGERYOTHERS.1WEIGHTOFPROCINTRAHOSPITALDEATHD30DEATHaaaa2redomidelaimiRENALIMPAIRMENTuaPULMONARYHYPERTENSIONlv1lv2SURGERYTHORACICAORTAPROCEDUREDIABETESONINSULINCLEARANCESURG
04.2502681.237539075PastYesoral therapyYesNo< 7 DNo0No0.0No0NoNoNoNoNo0Untreaded0Nono metatstasisNoNoNo91.0180.028.086420Sinusal10NoNo00119.061.152.040.057.0NoYesAo stenosisNoNoDegenerative/DystrophicNoNoNoNoNo0YesBioprosthesisNoNoNoNoNaNsingle non CABG0017160010000001061.1382351
140.51234722.124230067NoYesoral therapyNoNon STEMI> 90 DNo0Valvular1.0No0NoNoNoHemorragic strokeNo0No0NoNoNoNoNo85.0175.027.755102Sinusal30Noyes1072.0105.968.038.0NaNNoYesAoINoNoEndocarditisEndocarditisNoNoNoNo0YesBioprosthesisNoNoNoBentall bioOthers3 procedures009811000000110106.0020831
211.69532212.590731074PastYesNoNoNo< 7 DNo0No0.0No0NoNoNoNoNo0No0NoNoNoNoNo74.0177.023.620288Sinusal32NoNo00131.045.872.040.0NaNNoNoNoNoNoNaNNoAneurysmNoNoNo0YesBioprosthesisNoNoNoBentall bioOthers3 procedures1116150010000011045.8574051
38.1554084.889382068PastYesNoNoNo< 7 DNo0No0.0No0NoNoNoTIANo0No0NoNoNoNoNo72.0186.020.811655Sinusal30NoNo0073.087.267.035.0NaNNoYesNoNoNoOthersNoAneurysmNoNoNo0YesBioprosthesisNoNoNoBentall bioOthers3 procedures001090010000011087.3468491
48.1554085.502809068PastNooral therapyYesNo< 7 DNo0No0.0No0NoNoNoNoNo0No0No<5yearsYesNoNo64.0169.022.408179Sinusal30NoNo0088.064.355.025.0NaNNoYesAoINoNoCongenitalNoAneurysmNoNoNo0YesBioprosthesisNoNoNoBentall bioOthers3 procedures001090010000011064.4072731
54.6480144.430013056NoNoNoNoNo< 7 DNo0No0.0No0NoNoNoNoNo0No0NoNoNoNoNo64.0173.021.383942Sinusal30NoNo00102.064.760.0NaNNaNNoYesAo stenosisNoNoDegenerative/DystrophicNoAneurysmNoNoNo0YesBioprosthesisNoNoNoBentall bioOthers3 procedures00110010000011064.8282351
64.6480143.308568025NoNoNoNoNo< 7 DNo0No0.0No0NoNoNoNoNo0No0NoNoNoNoNo60.0167.021.513859Sinusal30NoNo0094.090.260.025.0NaNNoYesNoNoNoCongenitalNoAneurysmYesNoNo0YesBioprosthesisNoNoNoBentall bioOthers3 procedures00110010000011090.2872341
712.69408017.946738068PastYesNoNoNo< 7 DNo0No0.0No0NoYesNoNoNo0Yes treated1NoNoNoNoNo61.0167.021.872423Sinusal40NoNo00118.045.750.0NaNNaNNoYesAoINoNoDegenerative/DystrophicNoAneurysmNoNoNo0YesBioprosthesisNoNoNoBentall bio+FOPOthers3 procedures001090010000011045.7810171
821.26862315.390011074NoNoNoNoNo< 7 DNo0No0.0No0NoNoNoNoNo0No0NoNoNoNoNo74.0170.025.605536Sinusal40NoNo00112.053.655.0NaNNaNyesNoNoNoNoNaNNoDissectionNoNoYes1YesBioprosthesisNoNoYesBentall bio+PACOthers3 procedures1116150010000011053.6367861
95.2756744.552333061CurrentNoNoNoNo< 7 DNo0No0.0No0NoNoNoNoNo0No0NoNoNoNoNo83.0174.027.414454Sinusal30NoNo00102.079.060.0NaN65.0NoYesAoINoNoNaNNoAneurysmYesOthersNo0YesMechanicalNoNoNoBentall mecOthers3 procedures00320010000011079.0697061

Last rows

ES1ES2GENDERPAT_AAGEPATSMOKERARTERIAL HYPERTENSIONDIABETES STATUSDYSLIPIDEMIACORONARY ARTERY DISEASEACS<>PREVIOUSANGIOPLASTYRECENTMI_APREVIOUS CARDIAC SURGERYNUMBEREXTRACARDIAC ARTERIOPATHYEXTRACARDIAC ARTERIOPATHY_APREVIOUS CARDIAC FAILUREPREVIOUS ENDOCARDITISPREVIOUSEMBOLICEVENTPREVIOUS STROKENEUROLOGIC DYSFUNCTIONNEUROLOGIC DYSFUNCTION_ACOPDCOPDEUROSC_AULCERNEOPLASIAPREVIOUSRADIOTHERAPYCIRRHOSISON DIALYSISWEIGHTHEIGHTBMICARDIAC RHYTHMNYHACLASSANGORCLASSECCSCARDIACFAILUREACTIVEENDOCARDITISACTIVEENDOCARDITIS_BCRITICALPREOPERATIVESTATE_ACREATININECLEARANCECOCKLVEFPAPSYSTLVEFISOTOPICCORONARYARTERYDISEASEVALVULOPATHYSINGLEVALVULOPATHYPOLYVALVULOPATHYTRICUSPIDETIOLOGYREDO_AASCENDINGAORTACONGENITALHEARTDISEASEOTHERSURGENCYURGENCY_AVALVULARSURGERYAORTICMITRALTRISCUPIDCABGASCENDINGAORTASURGERYOTHERS.1WEIGHTOFPROCINTRAHOSPITALDEATHD30DEATHaaaa2redomidelaimiRENALIMPAIRMENTuaPULMONARYHYPERTENSIONlv1lv2SURGERYTHORACICAORTAPROCEDUREDIABETESONINSULINCLEARANCESURG
71514.2865932.724217057PastNoNoYesNo< 7 DYes0No0.0Lower Limbs1YesNoNoNoNo0No0NoNoNoNoNo70.0170.024.221453Sinusal40NoNo0094.075.940.0NaN45.0yesNoNoNoNoNaNNoNoNoPericarditisNo0NoNoNoNoNoNoOtherssingle non CABG00110010000101076.0244682
71521.5054311.640286050NoYesInsulinYesNo< 7 DNo0No0.0No0YesNoNoNoNo0No0NoNoNoNoNo114.0176.036.802686Sinusal30NoNo00148.085.278.0NaN74.0NoYesAo stenosisNoNoDegenerative/DystrophicNoNoNoPericarditisNo0YesMechanicalNoNoNoNoOthers2 procedures00110010000001185.2689191
71533.8370505.165886066NoNoNoYesNo< 7 DNo0No0.0No0YesNoNoIschemic strokeNo0Yes treated1YesNoNoNoNo88.0171.030.094730Sinusal40NoNo0084.095.250.033.0NaNNoYesOrg MRNoYesNaNNoNoNoPericarditisNo0YesNoBioprosthesisvalve repairNoNoOthers3 procedures11870010000001095.3542861
71541.5054316.147625043NoYesNoNoNo< 7 DNo0No0.0No0YesNoNoNoNo0No0NoNoNoNoNo55.0171.018.809206FA ou TSV40NoNo00138.047.563.046.0NaNNoYesOrg MRNoNoDegenerative/DystrophicNoNoNoNoNo0YesNoMechanicalvalve repairNoNoOthers3 procedures00110010000001047.5510871
715513.79228110.043518071CurrentYesoral therapyYesNon STEMI< 90 DYes1CABG1.0No0YesNoNoNoNo0Untreaded0NoNoNoNoNo66.0166.023.951227Sinusal23NoNo00178.031.455.0NaNNaNyesNoNoNoNoNaNCABGNoNoNoNo0NoNoNoNoYesNoOthers2 procedures0013121110000001031.4686522
71564.2502681.464295075NoYesoral therapyYesStable angina< 7 DNo0No0.0No0NoNoNoNoNo0No0No<5yearsNoNoNo83.0172.028.055706Sinusal22NoNo0075.088.470.0NaNNaNyesNoNoNoNoNaNNoNoNoPericarditisNo0NoNoNoNoYesNoOthers2 procedures0017160010000001088.4780002
71577.5428335.017429068PastYesoral therapyYesSTEMI> 90 DNo0No0.0Previous vascular surgery1NoNoNoNoNo0No0NoNoNoNoNo87.0174.028.735632Sinusal10NoNo00108.071.335.0NaNNaNyesYesTricuspidNoNoDegenerative/DystrophicNoNoNoNoNo0YesNoNovalve repairYesNoOthers3 procedures001090100000101071.3400001
71582.4416231.054651058CurrentNoNoNoNo< 7 DNo0No0.0No0NoNoNoNoNo0Yes treated1NoNoNoNoNo80.0166.029.031790Sinusal40NoNo0079.0102.065.0NaNNaNNoNoNoNoNoNaNNoNoNoPericarditisNo0NoNoNoNoNoNoOtherssingle non CABG001100100000010102.1367092
71593.9990665.941663056PastNoNoNoNo< 7 DNo0Valvular2.0No0YesNoNoNoNo0No0NoNoNoNoNo75.0169.026.259585FA ou TSV40NoNo00124.062.462.0NaNNaNNoYesTricuspidNoYesrheumaticAutreNoNoNoNo0YesNoNoBioprosthesisNoNoOthers2 procedures00111010000001062.4919351
716023.54046146.144126023NoNoNoNoNo< 7 DNo0Valvular1.0No0YesNoNoNoNo0No0NoNoNoNoNo90.0192.024.414062Sinusal40NoNo01113.0114.510.058.0NaNNoNoNoNoNoNaNAutreNoNoTransplantationNo0NoNoNoNoNoNoOtherssingle non CABG001110100010010114.6185842